Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add robisson/build-like-amazon-agent-skills --skill progressive-deploymentgit clone --depth 1 https://github.com/robisson/build-like-amazon-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/robisson/build-like-amazon-agent-skills/progressive-deployment)<a href="https://agentmods.dev/skills/robisson/build-like-amazon-agent-skills/progressive-deployment"><img src="https://agentmods.dev/badge/skills/robisson/build-like-amazon-agent-skills/progressive-deployment.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00022 | $0.01426 |
| Opus 5 | $0.00011 | $0.00713 |
| Sonnet 5 | $0.00004 | $0.00285 |
| Haiku 4.5 | $0.00002 | $0.00143 |
Grade A, and why
Progressive Deployment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Progressive Deployment
Overview
Every production change follows a staged rollout that expands blast radius gradually: One-Box → One-AZ → Regional → Global. Each stage has mandatory bake time during which alarms are monitored. Any alarm breach triggers automatic rollback to the last known-good state. The goal is to detect problems when they affect the fewest customers possible.
When to Use
- Every code deployment to production
- Configuration changes that affect runtime behavior
- Infrastructure changes (new instance types, scaling policies)
- Database schema migrations with application-level changes
- Any change that could impact customer-facing behavior
Amazon Context
At Amazon, no service deploys to all hosts simultaneously. The pipeline enforces progressive deployment because the cost of a bad deployment to 100% of hosts is measured in customer trust and revenue. A 1-box deployment that catches a bug costs almost nothing. A full-fleet deployment that causes a critical incident costs millions and erodes customer confidence. Teams that skip stages eventually cause high-severity events—this is not theoretical, it is observed repeatedly.
The Process
Stage 1: One-Box (Canary)
- Deploy to a single host in the lowest-traffic availability zone
- Route a small percentage of traffic (typically <1%) to this host
- Monitor for 30-60 minutes minimum (bake time)
- Compare metrics against the rest of the fleet:
- Latency p50, p99, p99.9
- Error rate (5xx, 4xx anomalies)
- CPU, memory, GC pauses
- Business metrics (conversion, success rate)
- Automated gate: proceed only if all metrics are within threshold
Stage 2: One-AZ
- Deploy to all hosts in one Availability Zone (~33% in a 3-AZ setup)
- Bake time: 60-120 minutes
- Monitor the same metrics at AZ level
- Watch for cross-AZ dependency issues
- Verify the AZ can handle full load if others need to absorb traffic during rollback
Stage 3: Regional
- Deploy to all hosts in one region
- Bake time: 2-4 hours (longer for low-traffic regions: 4-8 hours)
- Verify region-level metrics and cross-region replication
- Monitor for subtle issues that only appear at higher traffic volumes
- Choose initial region carefully: not the largest, not the smallest
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 132 lines · 22 tokens per session scan A 0fc84353718d
Progressive Deployment is a skill published in the GitHub repository robisson/build-like-amazon-agent-skills (14 stars, last pushed 3mo ago), licensed MIT. It adds 22 tokens to every session and 1,426 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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